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Simulation of main memory database parallel recovery 09

Simulation of main memory database parallel recovery

引用

2009 Spring Simulation Multiconference, SpringSim 2009

作者： Qin, Xiongpai Cao, Wei Wang, Shan Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China MOE Beijing100872 China

The paper describes the details of using J-SIM in main memory database parallel recovery simulation. In update intensive main memory database systems, I/O is still the dominant performance bottleneck. A proposal of parallel recovery scheme for large-scale update intensive main memory database systems is presented. Simulation provides a faster way of evaluating the new idea compared to actual system implementation. J-SIM is an open source discrete time simulation software package. The simulation implementation using J-SIM is elaborated in terms of resource modeling, transaction processing system modeling and workload modeling. Finally, with simulation results analyzed, the effectiveness of the parallel recovery scheme is verified and the feasibility of J-SIM's application in main memory database system simulation is demonstrated.

关键词： Recovery

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Lightweight data mining based database system self-optimization: A case study

Lightweight data mining based database system self-optimizat...

引用

Joint International Conference on Advances in data and Web Management, APWeb/WAIM 2009

作者： Qin, Xiongpai Cao, Wei Wang, Shan Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China MOE Beijing 100872 China

ISBN: (纸本)9783642006715

With the system becoming more complex and workloads becoming more fluctuating, it is very hard for DBA to quickly analyze performance data and optimize the system, self optimization is a promising technique. A data mining based optimization scheme for the lock table in database systems is presented. After trained with performance data, a neural network become intelligent enough to predict system performance with newly provided configuration parameters and performance data. During system running, performance data is collected continuously for a rule engine, which chooses the proper parameter of the lock table for adjusting, the rule engine relies on the trained neural network to precisely provide the amount of adjustment. The selected parameter is adjusted accordingly. The scheme is implemented and tested with TPC-C workload, system throughput increases by about 16 percent. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Locks (fasteners)

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Lawyer information integration and recommendation by multi-source information validation

Lawyer information integration and recommendation by multi-s...

引用

2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011

作者： Liu, Tao Fan, Biao Hu, He Du, Xiao-Yong Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9781457703065

On the internet, all-round lawyer information is located at separated information sources, which prevent web users from effective information acquisition. In order to build a unified view of separated, heterogeneous, and often redundant lawyer information, we propose a new information integration method using multi-source information cross-validation. Based on the unified integrated data, a lawyer recommendation system is built. Several key technologies are presented and evaluated, including the multi-source information acquisition and validation. Experimental results indicate the key techniques used in the system are effective for lawyer information integration and recommendation. © 2011 IEEE.

关键词： Information retrieval

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Utility-based anonymisation for dataset with multiple sensitive attributes

Utility-based anonymisation for dataset with multiple sensit...

引用

作者： Wang, Lixia Zhu, Qing Key Laboratory for Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China Beijing100872 China

Privacy-preserving data publication problem has attracted more and more attentions in recent years. A lot of related research works have been done towards dataset with single sensitive attribute. However, usually, original dataset contains more than one sensitive attribute. In this paper, we apply k-anonymity principle to solve the data publication problem for dataset with multiple sensitive attributes. We first cluster sensitive values based on a utility matrix. Then, we use a greedy strategy to partition tuples into equivalence classes. Our method can guarantee that the size of equivalence class is k except the last one, which reduces information loss. Also, we can guarantee the diversity of sensitive value in an equivalence class, which can protect privacy against the homogeneity attack. Experiments on a real dataset show that our method performs well on information loss, which indicates that we can guarantee data utility while protecting personal privacy. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Equivalence classes

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Virtualizing system and ordinary services in Windows-based OS-level virtual machines 11

Virtualizing system and ordinary services in Windows-based O...

引用

Proceedings of the 2011 ACM Symposium on Applied Computing

作者： Shan, Zhiyong Chiueh, Tzi-Cker Wang, Xin Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China China Stony Brook University United States

ISBN: (纸本)9781450301138

OS-level virtualization incurs smaller start-up and run-time overhead than HAL-based virtualization and thus forms an important building block for developing fault-tolerant and intrusion-tolerant applications. A complete implementation of OS-level virtualization on the Windows platform requires virtualization of Windows services, such as system services like the Remote Procedure Call Server Service (RPCSS), because they are essentially extensions of the kernel. As Windows system services work very differently from their counterparts on UNIX-style OS, i.e., daemons, and many of their implementation details are proprietary, virtualizing Windows system services turned out to be the most challenging technical barrier for OS-level virtualization for the Windows platform. In this paper, we describe a general technique to virtualize Windows services, and demonstrate its effectiveness by applying it to successfully virtualize a set of important Windows system services and ordinary services on different versions of Windows OS, including RPCSS, DcomLaunch, IIS service group, Tlntsvr, MySQL, Apache2.2, CiSvc, ImapiService, etc. © 2011 ACM.

关键词： Virtual machine

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Effective density queries for moving objects in road networks

Effective density queries for moving objects in road network...

引用

9th Asia-Pacific Web Conference/8th International Conference on Web-Age Information Management (APWeb/WAIM 2007)

作者： Lai, Caifeng Wang, Ling Chen, Jidong Meng, Xiaofeng Zeitouni, Karine School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering MOE PRISM Versailles Saint-Quentin University France

ISBN: (纸本)9783540724834

Recent research has focused on density queries for moving objects in highly dynamic scenarios. An area is dense if the number of moving objects it contains is above some threshold. Monitoring dense areas has applications in traffic control systems, bandwidth management, collision probability evaluation, etc. All existing methods, however, assume the objects moving in the Euclidean space. In this paper, we study the density queries in road networks, where density computation is determined by the length of the road segment and the number of objects on it. We define an effective road-network density query guaranteeing to obtain useful answers. We then propose the cluster-based algorithm for the efficient computation of density queries for objects moving in road networks. Extensive experimental results show that our methods achieve high efficiency and accuracy for finding the dense areas in road networks. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Object recognition

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Maintaining materialized relations incrementally to improve performance of ontology query

Maintaining materialized relations incrementally to improve ...

引用

7th International Conference on Web-Age Information Management Workshops, WAIM 2006

作者： Li, Man Du, Xiaoyong Wang, Shan School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE 100872 Beijing China

ISBN: (纸本)0769527051

For ontology-based applications, the efficiency of ontology query is vital. Different from existing approaches, the paper improves performance of ontology query by materializing some derived relations. Experimental results show that the integrated performance of ontology query can be improved greatly by maintaining materialized relations and the materialized relations technique has good scalability. Here the challenge is how to maintain the materialized relations incrementally with the update of ontologies. Because transitive relations are in common use in ontology, the paper proposes a novel algorithm for maintaining transitive materialized relations incrementally based on a special weighted materialized relation transitive graph, which can solve the coexistence problem of multiple derived paths better and proves the correctness of the algorithm. © 2006 IEEE.

关键词： Ontology

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COP: Privacy-preserving multidimensional partition in DAS paradigm 09

COP: Privacy-preserving multidimensional partition in DAS pa...

引用

2009 International Conference on Extending database Technology/International Conference on database Theory Workshops, EDBT/ICDT '09

作者： Wang, Jieping Du, Xiaoyong Wang, Haocong Yang, Pingping Key Laboratory of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9781605586502

database-as-a-Service (DAS) is an emerging database management paradigm wherein partition based index is an effective way to querying encrypted data. However, previous research either focuses on one-dimensional partition or ignores multidimensional data distribution characteristic, especially sparsity and locality. In this paper, we propose Cluster based Onion Partition (COP), which is designed to decrease both false positive and dead space at the same time. Basically, COP is composed of two steps. First, it partition covered space level by level, which is like peeling of onion;second, at each level, a clustering algorithm based on local density is proposed to achieve local optimal secure partition. Extensive experiments on real dataset and synthetic dataset show that COP is a secure multidimensional partition with much less efficiency loss than previous top down or bottom up counterparts. Copyright 2009 ACM.

关键词： database systems

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Region extreme value query in sensor networks

Region extreme value query in sensor networks

引用

6th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2009

作者： Wu, Zhongbo Chen, Hong School of Information Renmin University of China Beijing 100872 China MOE Key Lab. of Data Engineering and Knowledge Engineering Beijing 100872 China

ISBN: (纸本)9780769537351

Existing research on extreme value query in wireless sensor networks is mainly focus on finding out sensors with highest metric. Yet in most actually scenarios, people cares more about special network regions than detailed metric of some single nodes. We put forward region extreme query in sensor networks which don't consider a sensor node but a region as query unit. We formally define region extreme value query and discuss how they can be expressed using the SQL. Then we devise a distributed algorithm named DCA for in-network evaluation of region extreme value query in dynamic region, aiming at the minimization of power consumption. Experiments show that DCA has good performance. © 2009 IEEE.

关键词： Sensor nodes

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Reflection on the popularity of MapReduce and observation of its position in a unified big data platform

Reflection on the popularity of MapReduce and observation of...

引用

14th International Conference on Web-Age Information Management, WAIM 2013

作者： Qin, Xiongpai Qin, Biao Du, Xiaoyong Wang, Shan MOE Key Lab. of Data Engineering and Knowledge Engineering Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9783642395260

In recent years MapReduce has risen to be the de-facto tool for big data processing. MapReduce is a disruptive innovation. It has changed the landscape of database market, the landscape of technologies, as well as the landscape of saying power. The article will give a reflection on the popularity of the technique and some observations of its position in a unified big data platform. © 2013 Springer-Verlag.

关键词： MapReduce

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